Follow the money with ecommerce payment analytics
Payment analytics provide valuable ecommerce insights into customer behavior and financial performance, making it an essential tool for modern businesses looking to stay competitive. Every business transaction is the culmination of a series of processes that produce valuable data. But as our dev teams who build new digital payment solutions daily can attest: Not everyone in the industry is tapping the power of that data.
Sourcing the customer, assessing the desirability of a product, measuring brand recognition or loyalty, the flow of a digital storefront, even the performance of the checkout process itself — all of this data and more can be derived from an examination of the payment process; crunching that data can contribute insights that can lead to better processes, improved marketing, and, ultimately, more payments (i.e., sales!).
The benefits of data science in finance touch virtually every business, but none more so than ecommerce. We see this when developing fintech analytics, in large part due to one simple reason: hyper prevalence. To some extent, most businesses already use payment data for tracking traditional metrics like inventory volume, profit, and margin. The data generated by transactions can be used in far more specific functions for a much bigger impact.
This is where payment analytics comes in. Payment analytics in ecommerce come from studying transaction data and applying insights gained to different business functions. This analysis can create a much more in-depth profile of your customers through behavioral analysis; from there, you can uncover what’s working for them and what isn’t and adjust accordingly.
Leverage payment analytics
Customer lifetime value
Part of our expertise in developing ecommerce solutions is rooted in identifying advantages companies might not realize they have, and then helping them leverage those hidden advantages. There’s no better example than customer behavior, a wide-ranging spectrum: Some customers will only buy from you once, others become lifetime loyalists of the brand. As you develop a clear view of segments within your customer base, you can determine the customer lifetime value (CLV) of different types of buyers. By calculating your CLV, you can project how much each customer will spend over the length of their relationship with your business — therefore how much you should spend on attracting, engaging, and retaining them.
Calculating CLV is straightforward:
(Avg. product purchase value) x (Avg. rate of purchase) x (Avg. customer lifespan) = CLV
CLV underpins more accurate revenue projections using your existing customer base, tracking performance for campaigns aimed at repeat customers or recapturing lapsed customers, and improving your segmentation of customer groups to better inform your behavioral data.
Optimize marketing campaigns
Digital analytics can improve marketing efforts, but if you don’t leverage payment analytics as well, you lose a vital resource to inform future efforts: how much of your traffic converts to purchases.
The behavioral data that payment analytics provide means you can see how customers are reacting to marketing initiatives beyond engagement, it can show what’s driving actual sales. This can be as narrow in scope as seeing how an individual product is performing, or as far-reaching as seeing how competitor releases affect your overall conversion rates for a given time period.
Increase checkout completion rate
The average rate of abandonment for ecommerce purchases sits at just below 70 percent. The good news? There’s plenty of room to grow the rate of sales capture through the use of ecommerce payment analytics.
A major contributor to this abandonment rate is a clunky or counter-intuitive checkout process. “Quick and easy” is the mantra when it comes to checkout. Payment analytics allow you to field-test what actually works with customers.
Here’s an easy way to implement payment analytics operationally: Take the total number of successfully converted purchases in a given timeframe, cross-reference them with the total number of shopping carts created in that same timeframe, and then contrast your abandonment rate as you fine-tune your checkout process. Implementing simple but tangible changes like this can make a meaningful difference in the overall completion rate.
Improve transaction reliability
Chargebacks — when a credit card network refunds a customer claim of fraudulent behavior or a disputed transaction — are an irritating reality in retail. Payment analytics are the tonic that reduces the frequency at which they occur, which is a huge bonus given that chargebacks are expensive: With a single chargeback, a business loses the cost of the refund and the value of product itself, plus indirect costs like shipping expenses, time spent processing the transaction end-to-end, and the cost of acquiring the customer in the first place.
The answer to this pricey problem lies in analyzing what attributes of transactions most commonly show up in those ending in a chargeback. By identifying these elements, you can implement stronger fraud prevention safeguards to deter high-risk transactions.
An example: You run chargeback analytics as part of your payment analytics solution and find a high correlation between chargeback transactions made with a billing address from a different continent than the shipping address. Payment analytics solutions can set up automatic alerts for you or your loss prevention team to be notified, flagging the purchase for further investigation.
Better sales forecasting
Unparalleled accuracy in modeling future sales performance is a major competitive advantage companies gain by adopting payment analytics. By examining purchases YTD and YoY with an overlay of payment analysis, you can stop projecting based solely on past performance and start using data as it occurs in real time.
By adding in-the-moment behavioral data, your business and sales strategies can incorporate data-backed changes faster and allow for projections to not only include expected increases from those adjustments but create a better idea of what those increases will be.
The ease with which payment data can be cataloged also makes gathering the data for projections easier and quicker. That means you can plan and adjust with additional data without delaying or disrupting your entire sales strategy.
Faster, bigger, better: payment analytics for ecommerce
The benefits laid out here are applicable to any eCommerce business, but they’re not the only ones. By utilizing a payment analytics solution, you can also decide which elements of the solution bring the most value to your business and invest in customizing it accordingly.
In the same way that ecommerce is fundamental to modern retail and wholesale operations, data-backed solutions are part and parcel of a successful venture in the online retail landscape. Insights gleaned from analytics offer a rare benefit: enhancements both to the broader business and in specific functions. That rising tide of improved customer experience, higher conversion rates, and data-backed insights lifts all boats.
The only risk? Failing to catch the wave to begin with.